Comparing Calibrations of Similar Conically Scanning Window-Channel Microwave Radiometers

Wilheit, T. T.

doi:10.1109/tgrs.2012.2207122

Cited by 36 publications

(24 citation statements)

References 11 publications

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“…Also, a wider gap can be noticed between the average monthly emissivity values in the horizontal and vertical polarizations over desert. The horizontal polarization increase with increasing frequencies while the vertical polarization declines with the frequency increase (Yubao et al, 2014). This behavior was consistent among all investigated products.…”

Section: Resultssupporting

confidence: 83%

“…The efforts part of the Global Precipitation Measurement mission showed small differences between similar channels (but not identi-cal) of conical orbiting radiometers on two pairs of sensors, TMI/WindSat and TMI/AMSR-E. However, in some other channels, such as 37V, the differences between TMI and WindSat could reach 3 K (Wilheit, 2013), which can have a non-negligible influence on emissivity estimates. This difference causes about 0.01 difference in emissivity estimates, which is significant especially in regions where emissivity values are higher than 0.95 (Norouzi et al, 2012).…”

Section: Resultsmentioning

confidence: 99%

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Assessment of the consistency among global microwave land surface emissivity products

et al. 2015

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Abstract. The goal of this work is to intercompare four global land surface emissivity products over various landcover conditions to assess their consistency. The intercompared land emissivity products were generated over a 5-year period (2003)(2004)(2005)(2006)(2007) using observations from the Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and WindSat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity products were also compared to soil moisture estimates and a satellite-based vegetation index to assess their sensitivities to changes in land surface conditions.Results show the existence of systematic differences among the products. Also, it was noticed that emissivity values in each product have similar frequency dependency over different land-cover types. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower than the rest of the products across various land-cover conditions which may be attributed to the 01:30/13:30 LT overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analyzed products was lowest (less than 0.01) in rain forest regions for all products and highest at northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates, all products were similarly sensitive to changes in soil moisture and vegetation. The correlation between the emissivity polarization differences and normalized difference vegetation index (NDVI) values showed similar spatial distribution across the products, with values close to the unit except over densely vegetated and desert areas.

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Section: Resultssupporting

confidence: 83%

Section: Resultsmentioning

confidence: 99%

Assessment of the consistency among global microwave land surface emissivity products

et al. 2015

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“…Additional algorithms are used to compute geophysical parameters such as precipitation rate at the swath-level resolution (level 2, L2 data products). [For reference, a special collection of papers describing the L2 precipitation algorithms is appearing in the frequencies, bandwidths, polarizations, and view angles (Wilheit 2013(Wilheit , 2015Zavodsky et al 2013;Zhang et al 2011Zhang et al , 2016 Table 1). Figure 3 shows the extent of coverage provided by single 98-min orbits for each of the various radiometer types in the GPM constellation.…”

Section: Algorithms Data Pro D U Ct S Data Processing and Data Avmentioning

confidence: 99%

“…Sensor intercalibration between GMI and the partner sensors involves several steps, as described in Wilheit (2013), Wilheit et al (2015), and Berg et al (2016). Multiple independent approaches are compared during these steps, which help to identify flaws or limitations of a given approach, thus increasing confidence in the results and providing a measure of the uncertainty in the resulting calibration adjustments.…”

Section: Algorithms Data Pro D U Ct S Data Processing and Data Avmentioning

confidence: 99%

The Global Precipitation Measurement (GPM) Mission for Science and Society

Skofronick-Jackson

Petersen

Berg

et al. 2017

Bulletin of the American Meteorological Society

636

381

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Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h−1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.

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“…Such consistency can be ensured both by sensor intercalibration work [5][6][7] and model calibration studies. The last are based on radiative transfer calculations fulfilled for in situ matchup data collocated in time and space with the satellite measurements [8,9].…”

Section: Introductionmentioning

confidence: 99%

An Updated Geophysical Model for AMSR-E and SSMIS Brightness Temperature Simulations over Oceans

2014

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Abstract:In this study, we considered the geophysical model for microwave brightness temperature (BT) simulation for the Atmosphere-Ocean System under non-precipitating conditions. The model is presented as a combination of atmospheric absorption and ocean emission models. We validated this model for two satellite instruments-for Advanced Microwave Sounding Radiometer-Earth Observing System (AMSR-E) onboard Aqua satellite and for Special Sensor Microwave Imager/Sounder (SSMIS) onboard F16 satellite of Defense Meteorological Satellite Program (DMSP) series. We compared simulated BT values with satellite BT measurements for different combinations of various water vapor and oxygen absorption models and wind induced ocean emission models. A dataset of clear sky atmospheric and oceanic parameters, collocated in time and space with satellite measurements, was used for the comparison. We found the best model combination, providing the least root mean square error between calculations and measurements. A single combination of models ensured the best results for all considered radiometric channels. We also obtained the adjustments to simulated BT values, as averaged differences between the model simulations and satellite measurements. These adjustments can be used in any research based on modeling data for removing model/calibration inconsistencies. We demonstrated the application of the model by means of the development of the new algorithm for sea surface wind speed retrieval from AMSR-E data.

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Comparing Calibrations of Similar Conically Scanning Window-Channel Microwave Radiometers

Cited by 36 publications

References 11 publications

Assessment of the consistency among global microwave land surface emissivity products

Assessment of the consistency among global microwave land surface emissivity products

The Global Precipitation Measurement (GPM) Mission for Science and Society

An Updated Geophysical Model for AMSR-E and SSMIS Brightness Temperature Simulations over Oceans

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